Air Traffic Generation & Monte Carlo Simulation Engineer – DAA Risk Quantification

Alicante, España
#Join us in enabling drones to populate our skies

At Embention, we have been driven since 2007 by a clear mission: Enabling drones to populate our skies.

We provide more than 700 customers in 70 countries including internationally renowned companies such as Toyota, Amazon Prime Air, and Honda with Veronte autopilots, critical avionics, and software for their professional drones and eVTOLs. All our systems are developed in accordance with DO-178C, DO-254, and DO-160 standards, making us the only company in the sector certified by AESA and EASA as both a POA and APDOA.

The core of our company lies in our R&D team, made up of over 100 multidisciplinary engineers. Together with the rest of the organization, we are a team of 180 professionals united by a single goal: to innovate and push the boundaries of UAV technology.

Following a record-breaking 2025 marked by strong stock market performance, the launch of industrial production in the United Arab Emirates, and the establishment of a subsidiary in the United States, we are looking to continue expanding our team and driving continuous R&D development.

If you are passionate about our mission and want to be part of this journey, we are looking for you.

What would be your mission?

Your mission will be to implement and operate the statistical encounter simulation engine of the Detect and Avoid system, generating coherent synthetic air traffic and running large-scale Monte Carlo campaigns to quantify risk reduction, assess system robustness, and derive key technical requirements in BVLOS operations.

Which will be your responsibilities?

Implement probabilistic encounter models based on NRC or similar work.
Parameterise models with operational hypotheses.
Generate consistent synthetic air traffic.
Run massive Monte Carlo campaigns.
Invoke the GNC geometric module to evaluate each encounter.
Calculate risk ratios and statistical confidence levels.
Perform sensitivity analyses.
Derive technical system requirements from results.
Document model assumptions and validity limits.

️‍ ️ What do we need?

Training in aeronautical engineering, mathematics or physics.
Experience in stochastic simulation and Monte Carlo.
Solid knowledge of probability and applied statistics.
Scientific programming (Python, C++, Matlab).
Ability to perform rigorous quantitative analysis.

What do we value?

Previous experience with encounter models (Transport CanadaNRC, MIT, NASA, etc.).
Knowledge of UAS regulatory frameworks (SORA).
Experience in critical systems validation.

Embention is an equal opportunity employer. Recruitment decisions are made based on experience, qualifications, and alignment with role requirements.

Want to meet the team?